What to Read Next
We talk a lot at MIT SMR about the smart ways company leaders are sorting through avalanches of data to make better decisions. (Links to our most current articles on The New Intelligent Enterprise are here.)
In the world of medicine, analytics has a special kind of urgency. Technology gives doctors huge amounts of information about possible diagnosis, all of which they have to wade through and interpret. As patients, we hope they pick the right data to focus on (and as customers with co-pays, we hope they do it in a way that’s cost efficient).
Two recent conversations, by Thomas Goetz and Atul Gawande, get at how that hope we have as patients and bill payers could be better managed in the medical field through analytics.
Thomas Goetz, executive editor of Wired and author of “The Decision Tree: Taking Control of Your Health in the New Era of Personalized Medicine” (Rodale Books, 2010), spoke at the TEDMED 2010 conference last October on the topic “It’s time to redesign medical data.”
His thesis is that if you give people specific, detailed information about their health, they can start to see a vision of a path forward and the change in behavior it will take to get there. Seeing ends up being prescriptive.
The best way to give people specific information and get them on a path, Goetz says, is to make the information simple to understand. For instance:
“Blood test results are this great source of information. They’re packed with information. They’re just not for us. They’re not for people; they’re not for patients. They go right to doctors.
. . . What we did at Wired was we went, and I got our graphic design department to re-imagine these lab reports. So that’s what I want to walk you through. So this is the general blood work before, and this is the after, this is what we came up with. The after takes what was four pages — that previous slide was actually the first of four pages of data that’s just the general blood work. It goes on and on and on, all these values, all these numbers you don’t know. This is our one-page summary. We use the notion of color. It’s an amazing notion that color could be used. So on the top level you have your overall results, the things that might jump out at you from the fine print. Then you can drill down and understand how actually we put your level in context, and we use color to illustrate exactly where your value falls. In this case, this patient is slightly at risk of diabetes because of their glucose level.
. . . We need to recognize that the target of this information should not be the doctor, should not be the insurance company; it should be the patient. It’s the person who actually, in the end, is going to be having to change their lives and then start adopting new behaviors.”
The illustration above is a detail of Wired’s redesigned blood test results. You can see the image up close, along with images of a reworked heart disease test and prostate test, in the article “The Blood Test Gets a Makeover.” It’s posted online and appears in the December 2010 issue.
The second interesting conversation around health care is in the January 24 issue of The New Yorker. Atul Gawande, a surgeon who is also a staff writer profiles a Camden, N.J., physician and his efforts to ID the most expensive patients in the city.
Dr. Jeffrey Brenner’s goals are two-fold: to help get people get better service, and to lower health care costs. Gawande’s 10-page story examines many of the steps Brenner has taken using analytics:
“[Brenner] persuaded Camden’s three main hospitals to let him have access to their medical billing records. He transferred the reams of data files onto a desktop computer, spent weeks figuring out how to pull the chaos of information into a searchable database, and then started tabulating the emergency-room visits of victims of serious assault. He created maps showing where the crime victims lived. He pushed for policies that would let the Camden police chief assign shifts based on crime statistics — only to find himself in a showdown with the police unions.
. . . If he could find the people whose use of medical care was highest, he figured, he could do something to help them. If he helped them, he would also be lowering their health-care costs. And, if the stats approach to crime was right, targeting those with the highest health-care costs would help lower the entire city’s health-care costs. His calculations revealed that just one per cent of the hundred thousand people who make use of Camden’s medical facilities accounted for thirty per cent of its costs. That’s only a thousand people.”
As Gawande notes, “The new health-reform law — Obamacare — is betting big on the Brenners of the world. It says that we can afford to subsidize insurance for millions, remove the ability of private and public insurers to cut high-cost patients from their rolls, and improve the quality of care . . . Backers believe that, given this support, innovators like Brenner will transform health care everywhere.”